期刊文献+

一种超复数鲁棒相关图像配准算法 被引量:6

A Picture Matching Algorithm of Robust Hypercomplex Correlation
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摘要 为解决实际应用中彩色图像配准问题,针对已有的超复数互相关方法没有办法处理存在粗差的情况,在超复数互相关方法的基础上,结合鲁棒核函数,提出了一种超复数鲁棒相关的方法.该方法在频域中能使用快速傅里叶变换实现,在满足鲁棒性、实时性和准确性的同时,能通过遍历搜索去获得图像配准的全局解.即使在配准图像间存在粗差或者色彩旋转的情况下,该方法也能获得正确的配准结果.实验结果证明了该方法的有效性. A new approach that incorporates hypercomplex correlation with robusmess is presented for color image registration. Existing hypercomplex correlation method is not robust against outliers. The proposed method utilizes advantage of the FFT, therefore it can be robust, fast and exhaustive. The method also performs well even outliers or rotation in 3-D space exist. The experimental results verify the effectiveness of the proposed method.
出处 《复旦学报(自然科学版)》 CAS CSCD 北大核心 2007年第1期91-95,共5页 Journal of Fudan University:Natural Science
关键词 图像配准 超复数 互相关 鲁棒性 registration hypereomplex correlation robust
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参考文献6

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同被引文献65

  • 1倪国强,刘琼.多源图像配准技术分析与展望[J].光电工程,2004,31(9):1-6. 被引量:83
  • 2高富强,张帆.一种快速彩色图像匹配算法[J].计算机应用,2005,25(11):2604-2605. 被引量:15
  • 3刘贵喜,邵明礼,刘先红,朱东波.真实场景下视频运动目标自动提取方法[J].光学学报,2006,26(8):1150-1155. 被引量:32
  • 4王向军,王研,李智.基于特征角点的目标跟踪和快速识别算法研究[J].光学学报,2007,27(2):360-364. 被引量:48
  • 5B. Zitova, J. Flusser. Image registration methods: A survey[J]. Image and Vision Computing, 2003, (21): 977--1000
  • 6Brown L G. A survey of image registration techniques[J]. ACM Computing Surveys, 1992, 24(4) : 325-376
  • 7B. Srinivasa Reddy, B. N. Chatterji. A FFT based technique for translation, rotation, and scale-invariant image registration[C]. IEEE Transactions on Image Processing, 1996, 8 ( 5 ) :1266-1271
  • 8Jacqueline Le Moigne, William J. Campbell, Robert F. Cromp. An automated parallel image registration technique based on the correlation of wavelet features [C]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(8) : 1849-1864
  • 9George Lazaridis, Maria Petrou. Image registration using the walsh transform[C]. IEEE Transactions on Image Processing, 2006, 15(8) : 2343-2357
  • 10Alaa E. Abdel-Hakim, Aly A. Farag. CSIFT: A SIFT descriptor with color invariant characteristics [C]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2006, 2:1978-1983

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